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A Telemonitoring Service Supporting Preterm Newborns Care in a Neonatal Intensive Care Unit

机译:在新生儿重症监护室中支持早产新生儿的一项遥感服务

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Glucose concentration in blood, better known as glycemia, is a very underestimated physiological parameter in neonatal intensive care units. Its value is currently monitored by performing few measurements per day, acquired through heel pricks or arterial samplings. Unfortunately, the frequency of those samplings is quite low in preterm newborns, who are very low birth weight infants, due to their fragility. As a result, hyper- or hypo-glycemia events occurring between two separate measurements remain often unnoticed. A medical research group working at the University Hospital of Padova already proved the clinical benefits of continuous glucose monitoring for preterm newborns hospitalized in the neonatal intensive care unit. However, glucose data are still sampled through individual devices that are not integrated into a central monitoring system. Thus the health care staff has to visit regularly the cradles, watch the glycemia trends and pay attention to alarms. Our contribution deals with the implementation of a system based on mobile technologies that sends the data acquired through commercial glucometers to a central database, so that they become available in real time for the staff in the ward room. Moreover, we also integrated into that system an algorithm described in the literature for recommending the most appropriate glucose infusion rates based on the last readings of the patient. The system runs on an Android device and has been successfully tested in two different clinical trials involving twelve and five patients respectively.
机译:血液中的葡萄糖浓度,更好地称为糖血症,是新生儿重症监护单位中非常低估的生理参数。目前通过每天进行少数测量来监测其价值,通过鞋跟刺或动脉采样进行。不幸的是,由于其脆弱性,那些样品的频率是最低的新生儿,患者是非常低的出生体重婴儿。结果,在两个单独的测量之间发生的超高或血液血肿事件仍未被忽视。在帕多瓦大学工作的医学研究小组已经证明了在新生儿重症监护单位住院的早产新生儿的连续葡萄糖监测的临床益处。然而,葡萄糖数据仍然通过未集成到中央监控系统中的各个设备来采样。因此,医疗保健人员必须定期访问摇篮,观看糖类症趋势并注意警报。我们的贡献涉及基于移动技术的系统的实施,该技术将通过商业血糖仪获取的数据发送到中央数据库,因此它们可以实时为病房室内的工作人员提供。此外,我们还将其集成到该系统中,该系统在文献中描述的算法,用于推荐基于患者最后读数的最合适的葡萄糖输注速率。该系统在Android设备上运行,并在两种不同的临床试验中成功测试,涉及十二和五名患者。

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